| 2026 | HPDC | CoDL: A Framework for Studying Cross-Component Interference in Deep Learning Training Pipelines. | Druva Dhakshinamoorthy, Ray A. O. Sinurat, Nikoli Dryden, Arnab K. Paul, Hariharan Devarajan |
| 2025 | COMSNETS | Scheduling Big Machine Learning Tasks on Clusters of Heterogeneous Edge Devices. | Saumya Mathkar, Shreya Aiyer, Yashovardhan Bapat, Pinki, Arnab K. Paul, Vinayak Naik |
| 2025 | HiPC | Towards Mitigation of Latency and Forgetting in Vehicular Federated Continual Learning. | Harsh D. Chothani, Vimarsh Shah, Marichamy Kasi, Arnab K. Paul |
| 2025 | HiPC | Towards Building Trustworthy Data Provenance for Agentic Workflows. | Aishwarya Parab, Prakhar Pradhan, Manit Tanwar, Yogesh Simmhan, Arnab K. Paul |
| 2025 | ICDCN | User-based I/O Profiling for Leadership Scale HPC Workloads. | Ahmad Hossein Yazdani, Arnab K. Paul, Ahmad Maroof Karimi, Feiyi Wang, Ali Raza Butt |
| 2025 | Middleware | UnifyFL: Enabling Decentralized Cross-Silo Federated Learning. | Sarang S, Druva Dhakshinamoorthy, Aditya Shiva Sharma, Yuvraj Singh Bhadauria, Siddharth Chaitra Vivek, Arihant Bansal, Arnab K. Paul |
| 2024 | CLOUD | FedCaSe: Enhancing Federated Learning with Heterogeneity-aware Caching and Scheduling. | Redwan Ibne Seraj Khan, Arnab K. Paul, Yue Cheng, Xun Steve Jian, Ali Raza Butt |
| 2024 | CLUSTER | Studying the Effects of Asynchronous I/O on HPC I/O Patterns. | Arnav Gupta, Druva Dhakshinamoorthy, Arnab K. Paul |
| 2024 | HiPC | When Less is More: Achieving Faster Convergence in Distributed Edge Machine Learning. | Advik Raj Basani, Siddharth Chaitra Vivek, Advaith Krishna, Arnab K. Paul |
| 2024 | HiPC | Towards Pre-Training Data Evaluation for Client Selection in Federated Learning. | Vijay Dharmaji, Manit Tanwar, Subroto Majumder, M. Mustafa Rafique, Arnab K. Paul |
| 2024 | HiPC | Understanding Infrastructure Drift in Federated Learning Systems. | Shashank Rana, Vimarsh Shah, Aishwarya Jayashankar, Ayush Bhardwaj, Arnab K. Paul |
| 2023 | CLUSTER | An I/O Performance Evaluation of Varying CephFS Striping Patterns. | Debasmita Biswas, Sarah Neuwirth, Arnab K. Paul, Ali Raza Butt |
| 2023 | CLUSTER | Does Varying BeeGFS Configuration Affect the I/O Performance of HPC Workloads? | Arnav Borkar, Joel Tony, Hari Vamsi K. N, Tushar Barman, Yash Bhisikar, Sreenath T. M., Arnab K. Paul |
| 2023 | FAST | SHADE: Enable Fundamental Cacheability for Distributed Deep Learning Training. | Redwan Ibne Seraj Khan, Ahmad Hossein Yazdani, Yuqi Fu, Arnab K. Paul, Bo Ji, Xun Jian, Yue Cheng, Ali Raza Butt |
| 2023 | HiPC | HiPC 2023 Student Research Symposium (HiPC SRS 2023). | Arnab K. Paul, Suren Byna |
| 2023 | ICDCN | Characteristics of Deep Learning Workloads in Industry, Academic Institutions and National Laboratories. | Natasha Meena Joseph, S. Sai Vineet, Kunal Korgaonkar, Arnab K. Paul |
| 2023 | ICDCN | A Data-Centric Approach for Analyzing Large-Scale Deep Learning Applications. | S. Sai Vineet, Natasha Meena Joseph, Kunal Korgaonkar, Arnab K. Paul |
| 2023 | MASCOTS | Modeling the Impact of System-Level Parameters on I/O Performance of HPC Applications. | Debasmita Biswas, Arnab K. Paul, Sarah Neuwirth, Ali Raza Butt |
| 2023 | MASCOTS | Analyzing File Access Patterns on Large-Scale HPC Systems: Opportunities for File Prefetching. | Ahmad Maroof Karimi, Arnab K. Paul, Jong Youl Choi, Lipeng Wan, Feiyi Wang |
| 2022 | CLUSTER | Hvac: Removing I/O Bottleneck for Large-Scale Deep Learning Applications. | Awais Khan, Arnab K. Paul, Christopher Zimmer, Sarp Oral, Sajal Dash, Scott Atchley, Feiyi Wang |
| 2022 | HPDC | Machine Learning Assisted HPC Workload Trace Generation for Leadership Scale Storage Systems. | Arnab K. Paul, Jong Youl Choi, Ahmad Maroof Karimi, Feiyi Wang |